Categories are a foundation of cognition. Imagine if we could not abstract the essence of experiences and had to learn anew about every unique object and situation. We would probably have dysfunctions like those seen in neuropsychiatric disorders like autism and schizophrenia, which are marked by an impaired ability to generalize and extract meaning from experience. While a great deal is known about the cortical organization of the processing of bottom-up sensory information, virtually nothing is known about the respective roles of different cortical areas in top-down processing, particularly categorization. This is because few neurophysiological investigations have directly compared neural correlates of categories across brain areas and, importantly, no neurophysiological study has manipulated the attributes that determine the level of categorization. We will do so while directly comparing neural activity in the prefrontal cortex (PFC) and lateral intraparietal area (LIP), two cortical areas that human and monkey studies indicate are engaged during visual categorization. We will test the hypothesis that the PFC plays the central role in extracting learned categories or that either the PFC or LIP will play the leading role in categorization depending on the level of category demand. We will record simultaneously two brain regions known to have neural correlates of categories the PFC and LIP in a task known to activate both areas in humans (dot pattern categorization). Monkeys will classify category exemplars formed by distorting prototypes of arbitrary dot patterns. Because dot patterns can be parametrically varied, we can manipulate fundamental category properties (abstractness, complexity, and number of alternative category decisions). Because virtually nothing is known about the how these manipulations affect the neural correlates of categories, any pattern of results will be informative and provide insight into the fundamental mechanisms by which the brain adds meaning to the world.